ReviewJournal of spine surgery (Hong Kong)2026
Cost-effectiveness and evidence gaps of advanced technologies in lumbar spine surgery: a scoping review.
Review in Journal of spine surgery (Hong Kong), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Robotic guidance, augmented reality (AR), and emerging artificial intelligence (AI) technologies are increasingly integrated into lumbar spine surgery. While improvements in technical accuracy and perioperative metrics have been widely reported, the economic value and feasibility of adopting these technologies remain uncertain. This scoping review aimed to map and synthesize evidence on cost-effectiveness, economic evaluation approaches, and adoption-related gaps associated with robotic-, AR-, and AI-assisted lumbar spine surgery. Methods: A scoping review was conducted in accordance with PRISMA-ScR guidelines. Scopus, PubMed, Embase, and Web of Science were searched from inception through May 2025 for human studies evaluating robotic, AR, or AI technologies in lumbar spine surgery that reported clinical or economic outcomes. Data on study design, technology type, clinical outcomes, complications, and cost-related measures were extracted and synthesized narratively, with emphasis on economic outcomes and implementation considerations. Results: Fourteen studies met the inclusion criteria. Robotic-assisted surgery consistently demonstrated higher pedicle screw accuracy and modest reductions in blood loss and hospital length of stay (LOS) compared with freehand or navigated techniques, although operative time was frequently increased. Economic findings were heterogeneous: modeling studies and select institutional analyses suggested potential cost savings at high surgical volumes, whereas large administrative database studies reported higher hospital charges and increased transfusion rates in robotic cases. AR studies were limited to small case series and narrative reviews, reporting favorable perioperative metrics without formal economic evaluation. AI applications were confined to prognostic modeling, with no studies reporting patient-level clinical or cost outcomes. Conclusions: Evidence supporting the cost-effectiveness of advanced technologies in lumbar spine surgery remains inconsistent and highly context dependent. While robotic systems offer technical advantages, their economic value varies by institutional factors such as surgical volume and efficiency. Standardized economic evaluations and implementation-focused studies are needed to guide value-based adoption of robotic, AR, and AI technologies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.